Tornike Mzhavia
About Tornike Mzhavia
Tornike Mzhavia is a Lead Software Engineer specializing in Machine Learning at Thomson Reuters, with over a decade of experience in various industries. He holds a Bachelor's degree in Computer Science and a Master's degree in Automation Engineering, and has worked in roles ranging from Data Scientist to AI Developer across multiple companies.
Work at Thomson Reuters
Tornike Mzhavia currently serves as a Lead Software Engineer specializing in Machine Learning at Thomson Reuters. He has held this position since 2022 and is based in London, England. In this role, he focuses on developing and implementing machine learning solutions to enhance the company's data processing capabilities.
Previous Experience in Data Science
Before joining Thomson Reuters, Tornike Mzhavia worked as a Data Scientist at Skillific from 2017 to 2020, contributing for three years. He also briefly worked in 2016 as a Data Scientist for four months in Estonia. His experience in data science includes roles that involved analyzing data and building predictive models.
Background in Education and Expertise
Tornike Mzhavia holds a Bachelor's degree in Computer Science from Tbilisi State University, which he completed from 2009 to 2014. He furthered his education by obtaining a Master of Science (M.Sc.) in Mechatronics, Robotics, and Automation Engineering from TalTech – Tallinn University of Technology between 2014 and 2016. His academic background supports his expertise in machine learning and software engineering.
Experience in Cloud Architecture and AI Development
In addition to his current role, Tornike Mzhavia has worked as a Cloud and ML Architect at CellKey since 2021, operating remotely from Seoul, South Korea. He has also held positions such as a Data Engineer at NGX Bio and an AI Developer at Neiron. His diverse experience spans over a decade and includes sectors like fraud detection, bioinformatics, and automation.
Teaching and Skills in Machine Learning
Tornike Mzhavia has experience in teaching machine learning and computer science, sharing his knowledge with others in the field. He possesses strong skills in Cloud architecture, Artificial Intelligence, Python, and .NET, which are essential for his roles in software engineering and data science.